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PRODID:IEEE vTools.Events//EN
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TZID:Asia/Kolkata
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TZOFFSETFROM:+0630
TZOFFSETTO:+0530
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DTSTAMP:20250107T111957Z
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DTSTART;TZID=Asia/Kolkata:20240613T090000
DTEND;TZID=Asia/Kolkata:20240613T094500
DESCRIPTION:Application of Machine Learning in Semiconductor-Based Devices\
 n\nMachine learning (ML) is revolutionizing semiconductor device design\, 
 manufacturing\, and performance optimization. In design\, ML models accele
 rate the development of advanced materials\, predict device behavior\, and
  optimize parameters for efficiency and performance. During manufacturing\
 , ML enhances process control by identifying defects\, optimizing yield\, 
 and improving wafer fabrication through predictive analytics and anomaly d
 etection. For device performance\, ML enables intelligent tuning\, adaptiv
 e control systems\, and predictive maintenance in applications like power 
 electronics\, photonic circuits\, and sensors. ML also plays a crucial rol
 e in accelerating R&D for next-generation semiconductors\, fostering innov
 ations in energy efficiency\, speed\, and scalability.\n\nSrinagar\, Jammu
  & Kashmir\, India
LOCATION:Srinagar\, Jammu & Kashmir\, India
ORGANIZER:alahgere@iitk.ac.in
SEQUENCE:7
SUMMARY:Application of Machine learning in Semiconductor based devices
URL;VALUE=URI:https://events.vtools.ieee.org/m/460878
X-ALT-DESC:Description: <br /><h3>Application of Machine Learning in Semico
 nductor-Based Devices</h3>\n<p>Machine learning (ML) is revolutionizing se
 miconductor device design\, manufacturing\, and performance optimization. 
 In design\, ML models accelerate the development of advanced materials\, p
 redict device behavior\, and optimize parameters for efficiency and perfor
 mance. During manufacturing\, ML enhances process control by identifying d
 efects\, optimizing yield\, and improving wafer fabrication through predic
 tive analytics and anomaly detection. For device performance\, ML enables 
 intelligent tuning\, adaptive control systems\, and predictive maintenance
  in applications like power electronics\, photonic circuits\, and sensors.
  ML also plays a crucial role in accelerating R&amp\;D for next-generation
  semiconductors\, fostering innovations in energy efficiency\, speed\, and
  scalability.</p>
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